A model for tree-crops prediction in Sentinel-2 imagery

The model was designed for tree-crops semantic-segmentation and created using the AI4Copernicus service: “Deep network for pixel-level classification of S2 patches"

ML Model

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Developed by

Sense P.C

License

Creative Commons Attribution 4.0 International License

Main Characteristic

The U-net model was created for the SandMap platform, a tangible GIS educational platform which aims to inform the students and citizens about the importance of precision agriculture and the relative cutting-edge technology in order to automate significant processes such as classification and localization of crops using AI. This model allows AI engineers and individuals to predict tree-crops regions in Sentinel-2 imagery.

Technical Categories

Computer vision Machine learning

Business Categories

Agriculture Earth Observation

Keywords